Assisted Free Form Decision Definition Using Rules Vocabulary

ABSTRACT

A method of decision definition using a rules vocabulary includes: receiving free form input; identifying terms contained within the free form input; searching the rules vocabulary objects for terms; responsive to the term being found, obtaining input from a user as to whether to use the found term; responsive to the term not being found; searching the rules vocabulary attributes for terms having attributes corresponding to the term; responsive to the term being found, obtaining input from a user as to whether to use the found term; and refactoring the free form input with the found term accepted by the user. The method also includes updating the rules vocabulary with the term identified in the free form input as a synonym for the term found in said rules vocabulary. One embodiment further provides a method of determining semantic equivalence between a plurality of rules using a rules database having preferred terms.

PRIORITY CLAIM

The present application claims benefit of priority under 35 USC §120 and§365 to the previously filed United Kingdom Patent Application No.1210811.4 titled, “Assisted Free Form Decision Definition Using RulesVocabulary” with a priority date of Jun. 19, 2012. The content of thatapplication is incorporated by reference herein.

BACKGROUND

1. Technical Field

The present disclosure relates to computer-based decision definition andin particular to computer-based decision definition using a rulesvocabulary.

2. Description of the Related Art

“Information Models and Systems”, found athttp://dret.net/lectures/infosys-ws06/infosys, discloses the semanticstructure of documents including the use of rules. Rules are a formal orrefined statement of a requirement that is expressed in atechnology-independent fashion. The article also discloses the use of acontrolled vocabulary that is a standardised set of terms to helpsearchers find information. A closed vocabulary can be thought of as afixed or closed dictionary in which all rules are defined using the sameset of terms. The article does not disclose how such a closed vocabularymight be built.

Another document provided athttp://docs.oracle.com/html/E27987_(—)01/toc.htm discloses the conceptof transforming natural language expressions into executable rules.Rules are authored by a user using a word processor to define the rule.The building of a vocabulary is not disclosed.

The document found athttp://www.prweb.com/releases/2006/07/prweb410401.htm discloses thewriting of rules in natural language in a word processor, a drawingprogram, or a spreadsheet. A rule is defined based on an existing rulevocabulary. Keywords are not added or amended during the rule writingprocess.

“Evaluating Interfaces for Privacy Policy Rule Authoring” (Karet et al.,CHI 2006 Proceedings, April 22-27 2006, Montreal, Canada) disclosesadding constraints to personal information at the policy level ratherthan at the operational vocabulary and rules levels. The document doesnot disclose authoring of rules using an expanded operationalvocabulary.

“Building natural language interfaces for rule-based expert systems”,Proceedings of the 10th international joint conference on Artificialintelligence—Volume 2 (IJCAI'87), Vol. 2. Morgan Kaufmann PublishersInc., San Francisco, Calif., USA, 682-687 by Galina Datskovsky Moerdler,Kathleen R. McKeown, and J. Robert Ensor, 1987 discloses the mapping ofa natural language into an expert system. The article does not disclosethe evolution of vocabulary and rules in the expert system itself.

BRIEF SUMMARY

Embodiments of the present disclosure provide a computer-implementedmethod of decision definition using a rules vocabulary, the methodcomprising: receiving free form input; identifying terms containedwithin the free form input; searching the rules vocabulary objects forterms; responsive to the term being found, obtaining input from a useras to whether to use the found term; responsive to the term not beingfound; searching the rules vocabulary attributes for terms havingattributes corresponding to the term; responsive to the term beingfound, obtaining input from a user as to whether to use the found term;and refactoring the free form input with the found term accepted by theuser. The steps of this method provide the advantage of allowing an enduser to generate rules in free from, but also allowing the use of adefined rules vocabulary with the benefits of a consistent usage ofvocabulary and of attributes associated with the vocabulary.

In one embodiment, the terms are any of objects, attributes, values,relationships or verbs.

In one embodiment, the method further comprises the step of updating therules vocabulary with the term identified in the free form input. Thisupdating has the advantage of allowing the consistent rules vocabularyto be added to if there really is no term corresponding to the term usedby the user pre-existing in the vocabulary.

In one embodiment, the method further comprises the step of updating therules vocabulary with the term identified in the free form input as asynonym for the term found in the rules vocabulary. This updating hasthe advantage of allowing the user to use a term which is part of theirnatural language, but also having the advantage of using a term which isconsistent with that used by other users.

In one embodiment, responsive to input from the user to not use the termfound during the search of the rule vocabulary objects for terms, therules vocabulary attributes are searched for terms having attributescorresponding to the term. This search has the advantage that if anobject corresponding to the object in the input from the user is notfound during a search for objects, then a corresponding object may befound by comparing the attributes of pre-existing objects in the rulesdatabase.

Embodiments of the present disclosure further provide a method ofdetermining semantic equivalence between a plurality of rules using arules database having preferred terms, comprising the steps of:identifying at least one of objects, attributes, values, relationshipsor verbs in each of the plurality of rules; replacing each of the atleast one of objects, attributes, values, relationships, and verbs ineach of the plurality of rules with a preferred term found in the rulesdatabase to form a plurality of amended rules; and comparing a first ofthe plurality of amended rules and a second of the plurality of amendedrules; responsive to the comparison being true, then identifying thefirst of the plurality of rules and the second of the plurality of rulesas being equivalent. This sequence of processes has the advantage ofallowing a consistent set of rules to be used without duplication ofrules but without restricting the terms used by a user.

In one embodiment the method further comprises the step of replacinggeneralised terms with semantically equivalent terms.

Embodiments of the present disclosure also provide a system and acomputer program product for carrying out the method functions describedabove.

The above summary contains simplifications, generalizations andomissions of detail and is not intended as a comprehensive descriptionof the claimed subject matter but, rather, is intended to provide abrief overview of some of the functionality associated therewith. Othersystems, methods, functionality, features and advantages of the claimedsubject matter will be or will become apparent to one with skill in theart upon examination of the following figures and detailed writtendescription.

BRIEF DESCRIPTION OF THE DRAWINGS

The description of the illustrative embodiments can be read inconjunction with the accompanying figures. It will be appreciated thatfor simplicity and clarity of illustration, elements illustrated in thefigures have not necessarily been drawn to scale. For example, thedimensions of some of the elements are exaggerated relative to otherelements. Embodiments incorporating teachings of the present disclosureare shown and described with respect to the figures presented herein, inwhich:

FIG. 1 shows three rules being processed to update a rules vocabulary;

FIG. 2 shows the rules vocabulary of FIG. 1;

FIG. 3 shows a local vocabulary associated with one of the rules of FIG.1 before consolidation with the rules vocabulary of FIG. 1;

FIG. 4 shows the rules vocabulary of FIG. 1 before consolidation withthe local vocabulary associated with one of the rules of FIG. 1;

FIG. 5 shows a flow diagram of an embodiment of the disclosure in whicha rules vocabulary is searched for objects and for attributes;

FIG. 6 shows the local vocabulary of FIG. 3 after consolidation with therules vocabulary of FIG. 4;

FIG. 7 shows the rules vocabulary of FIG. 4 after consolidation with thelocal vocabulary of FIG. 3;

FIG. 8 shows another embodiment of the disclosure in which a user isprompted as to whether to add a found term as a synonym;

FIG. 9 shows an embodiment of the present disclosure in which aplurality of rules is compared for equivalence; and

FIG. 10 is a block diagram illustration of an example data processingsystem within which the various features of the described embodimentscan be implemented.

DETAILED DESCRIPTION

In the following detailed description of exemplary embodiments of thedisclosure, specific exemplary embodiments in which the disclosure maybe practiced are described in sufficient detail to enable those skilledin the art to practice the disclosure, and it is to be understood thatother embodiments may be utilized and that logical, architectural,programmatic, mechanical, electrical and other changes may be madewithout departing from the spirit or scope of the present disclosure.The following detailed description is, therefore, not to be taken in alimiting sense, and the scope of the present disclosure is defined bythe appended claims and equivalents thereof.

In the following detailed description, numerous specific details such asspecific method orders, structures, elements, and connections have beenset forth. It is to be understood however that these and other specificdetails need not be utilized to practice embodiments of the presentdisclosure. In other circumstances, well-known structures, elements, orconnections have been omitted, or have not been described in particulardetail in order to avoid unnecessarily obscuring this description.

References within the specification to “one embodiment,” “anembodiment,” or “embodiments” are intended to indicate that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the presentdisclosure. The appearance of such phrases in various places within thespecification are not necessarily all referring to the same embodiment,nor are separate or alternative embodiments mutually exclusive of otherembodiments. Moreover, various features are described which may beexhibited by some embodiments and not by others. Similarly, variousrequirements are described which may be requirements for someembodiments but not other embodiments.

It is understood that the use of specific component, device and/orparameter names (such as those of the executing utility/logic describedherein) are for example only and not meant to imply any limitations onthe disclosure. The disclosure may thus be implemented with differentnomenclature/terminology utilized to describe thecomponents/devices/parameters herein, without limitation. Each termutilized herein is to be given its broadest interpretation given thecontext in which that terms is utilized.

Those of ordinary skill in the art will appreciate that the hardwarecomponents and basic configuration depicted in the presented figures mayvary. For example, the illustrative components within the dataprocessing system (DPS 1000, FIG. 10) are not intended to be exhaustive,but rather are representative to highlight essential components that areutilized to implement the present disclosure. For example, otherdevices/components may be used in addition to or in place of thehardware depicted. The depicted example is not meant to implyarchitectural or other limitations with respect to the presentlydescribed embodiments and/or the general disclosure. The data processingsystem depicted in FIG. 10 may be, for example, an IBM eServer pSeriessystem, a product of International Business Machines Corporation inArmonk, N.Y., running the Advanced Interactive Executive (AIX) operatingsystem or LINUX operating system.

Referring to FIG. 1, rule 1 102, rule 2 104 and rule 3 106 are shown.Each of the rules is a free form sentence in natural language describinga particular course of action which should be followed. Although FIG. 1shows three rules, there may be any number of rules. An example might be“When the customer is less than 18 years old then reject the order”.Another example might be “When the purchaser's age is more than 65 thenapply 5% elderly person's discount to order”. These rules are beingauthored by a user to, for example, allow them to be used to implementpolicies across a broad computing system or to allow a global policy tobe implemented across different applications and contexts. When therules are authored, they are then used to update a rules vocabulary 108.

Rules can be broken down into terms such as, for example, objects andattributes. Attributes may have values such as “18”, “John Doe”, “2BE”or “NOT2B” or they may reference other concepts such as “brother of . .. ”. Using the first example above, the rule “When the customer is lessthan 18 years old then reject the order” can be broken down as follows:

Similarly, using the second example above, the rule “When thepurchaser's age is more than 65 apply 5% elderly person's discount toorder” can be broken down as follows:

FIG. 2 shows a rules vocabulary 108 comprising terms 202. Terms 202 are,for example, objects or attributes or relationships such as “brother of. . . ”. Although seven terms are shown, there may be a single term orany number of terms. Rules vocabularies 108 may be general purpose orthey may be specialised for particular purposes, users, industries orthe like.

FIG. 3 shows a local vocabulary for the second example above. Thevocabulary is “local” because that is the scope of the sharing, i.e. thelocal vocabulary is a subset of the global vocabulary that is local tothe user of the vocabulary. A first object “Purchaser” is shown. Theobject “Purchaser” has one attribute “age”. A second object “Order” isalso shown. The object “Order” also has one attribute “discount”. Thesecorrespond with the terms in the breakdown of the rule in the secondexample above.

FIG. 4 shows an example rules vocabulary 108 containing terms 202. Afirst object “Customer” is shown. That object has a synonym of “Client”,so that either term can be used interchangeably. The object “Customer”has three attributes, “age”, “name” and “id”. The attribute “age” has asynonym of “d.o.b.” (date of birth) and the attribute “name” has asynonym of “surname”. The object “Vehicle” has four attributes, “age”,“license number”, “make” and “model”. The object “Order” has oneattribute “order number”.

FIG. 5 shows a flow diagram of an embodiment of the present disclosureused to update a rules vocabulary 108, such as that shown in FIG. 1,from free form input rules 102, 104, 106. The process starts at step502. Free form input, such as the rules 102, 104, 106 described in thetwo examples above is received from a user at step 504. At step 506, thefree form input is analysed to identify terms such as objects,attributes, values and relationships. In the second example above, theobject “Purchaser” has an attribute of “age” and the object “order” hasan attribute of “discount”. This analysis can be done by known methodssuch as syntactic analysis or by parsing or by pattern matching. At step508, the terms 202 in the rules vocabulary 108 are searched for termscorresponding to the objects found during the analysis step 506. In thisexample, the search is for the objects “Purchaser” and “order”.

At step 510, if the search is successful and the object is found in therules vocabulary 108, then the found object is presented to the user asa candidate for the object in the rule 102, 104, 106. In the secondexample above, the search of the rules database 108 for the object“Purchaser” will find the object “Customer”, which already has a synonymof “Client”.

At step 518, the user is presented with the object found and itsassociated attributes, that is “Customer”, with a synonym of “Client”and attributes of “age”, “name” and “id”. The user is asked whether thisobject is the one that should be used, i.e. should “Customer” be usedinstead of “Purchaser”, optionally should “Purchaser” be added as asynonym of “Customer” or optionally should “Purchaser” not be treated asthe same as or a synonym of “Customer”, i.e. “Purchaser” and “Customer”are to be treated as disjoint. At step 522, if the user agrees that thisobject (“Customer”) is the one that should be used, or that “Purchaser”be added as a synonym of “Customer”, then the rule is reworded using theobject “Customer” in place of “Purchaser”. In one embodiment, not shownin FIG. 5, the user is offered the option of adding the searched term tothe existing vocabulary. The process then ends at step 524.

If the search at step 508 is unsuccessful and the object is not found inthe rules vocabulary 108, then at step 512 another search of theattributes in the rules database 108 is carried out for attributescorresponding to those found in the rule. In the second example above,the attributes are “age” and “discount”. At step 514, if the search issuccessful and a corresponding attribute is found in the rulesvocabulary 108, then the found attribute is presented, at step 520, tothe user as a candidate for the attribute in the rule 102. In the secondexample above, the search of the rules database 108 will find theattribute “age”, associated with the object “Customer” in addition tothe attribute “age”, associated with the object “Vehicle”. The userselects which of the two objects is the appropriate one to use. In apreferred embodiment, not shown in FIG. 5, the user is offered theoption of adding the searched term to the existing vocabulary. At step522, if the user agrees that this object (“Customer”) is the one thatshould be used, or that “Purchaser” be added as a synonym of “Customer”,then the rule is reworded using the object “Customer” in place of“Purchaser”. The process then ends at step 524.

At step 514, if the search is unsuccessful and a corresponding attributeis not found in the rules vocabulary 108, the process then ends at step524.

FIG. 6 shows the local vocabulary of FIG. 3 used in the second exampleabove after consolidation with the rules vocabulary of FIG. 4. The firstobject “Purchaser” having one attribute “age” has been replaced by afirst object “Customer” having three attributes “age, “name” and “id”.The user entered “Purchaser” as an object, but a search of the rulesvocabulary found “Customer” as an object which already existed in therules vocabulary and which was likely to be an equivalent object. Theuser agreed at step 522 of the process shown in FIG. 5 that the termshould be replaced. As it is already known that the object “Customer” inthe rules vocabulary has attributes of “name” and “id” as well as “age”,then these additional attributes are added to the local vocabulary forthe object “Customer”. The synonyms “d.o.b.” and “surname” found in therules vocabulary have been added to the attributes “age” and “name”respectively.

A second object “Order” is also shown in FIG. 3 having a singleattribute “discount”. The user entered “Order” as an object and the termwas found. However, the object “Order” in the rules vocabulary had twoattributes “discount” and “order number”. As it is already known thatthe object “Order” in the rules vocabulary has attributes of “ordernumber” as well as “discount”, then in the local vocabulary of FIG. 6,this additional attribute is added to the local vocabulary for theobject “Order”.

FIG. 7 shows the example rules vocabulary of FIG. 4 used in the secondexample above after consolidation with the local vocabulary of FIG. 3. Afirst object “Customer” is shown having a synonym of “Client”, so thateither term can be used interchangeably. A further synonym of“Purchaser” has been added so that this can also be usedinterchangeably. The object “Order” is shown having an attribute “ordernumber”. A further attribute of “discount” has been added to the object“Order”.

FIG. 8 shows a flow diagram of another embodiment of the presentdisclosure in which a user is prompted as to whether or not to add afound term as a synonym and also in which a search of attributes in therules vocabulary 108 is completed if a user does not accept a term foundin the search of the rules vocabulary 108 for objects. The step 510 inFIG. 8 is the same step 510 as shown in FIG. 5. Similarly, steps 512,514, 518, 520, 522 and 524 are the same steps as shown in FIG. 5.

At step 518, if the user does not accept the term, then processingproceeds to step 512 where the vocabulary term attributes are searchedfor attributes which correspond to the searched term. If the user doesaccept the term, then at step 802, input is obtained from the user as towhether to add the term accepted by the user at step 518 to the rulesvocabulary 108 as a synonym. Processing then continues at step 522described above with reference to FIG. 5.

At step 520, if the user does not accept the term, then processing endsat step 524. If the user does accept the term, at step 804, input isobtained from the user as to whether to add the term accepted by theuser at step 520 to the rules vocabulary 108 as a synonym. Processingthen continues at step 522 described above with reference to FIG. 5.

In another embodiment of the disclosure, the rules vocabulary 108 issearched for verbs, such as “reject” or “approve” instead of attributes,such as “age”. In a variation of this embodiment, the rules vocabularyis searched for both attributes and for verbs.

In a further embodiment of the disclosure, the rules vocabulary 108 issearched for synonyms of attributes in the same way as synonyms ofobjects are searched. In a variation of this embodiment, synonyms ofverbs are searched instead of synonyms for attributes, or as well assynonyms for attributes.

In another embodiment of the disclosure, semantically equivalent ruleswhich infer the same conditional statement can be identified. Forexample, the two rules:

Referring to FIG. 9, the process is started at step 902. In order todetermine whether two rules are semantically equivalent, the rules firsthave their objects, values and verbs identified at step 904. Anycombination or permutation of objects, values, verbs or other term suchas relationships may be identified, but for the following example,objects, values and verbs will be identified.

In the first rule, the term “customer” is identified as an object, thenumber “18 years” is identified as a value, the term “reject” isidentified as a verb, and the term “order” is identified as an object.In the second rule, the term “client” is identified as an object, thenumber “18” is identified as a value, the term “refuse” is identified asa verb, and the term “sale” is identified as an object.

At step 906, each object, value or verb is replaced in each of the rulesby the preferred term, i.e. if the object, value or verb used in therule is identified as a synonym, then that usage is replaced by the termin the rules database with which it is associated with.

In the first rule, “customer” is a preferred term and so the term“customer” remains. The number “18 years” is identified as a synonym for“18” and so “18 years” is replaced by “18”. The verb “reject” isidentified as a synonym for “refuse” and so the verb “reject” isreplaced by “refuse”. The object “order” is identified as a preferredterm and so it remains. The first rule now reads “When the customer isless than 18 then refuse the order”.

In the second rule, “client” is identified as a synonym for “customer”and so “client” is replaced by “customer”. The number “18” is identifiedas a preferred term and so “18” remains. The verb “refuse” is identifiedas a preferred term and so the verb “refuse” remains. The object “sale”is identified as a synonym for “order” and so “sale” is replaced with“order”. The second rule now reads “If the customer's age is not greaterthan 18 then refuse the order”.

Either before or after the replacement of the terms, some generalizedterms are replaced with semantically equivalent preferred terms. Forexample, “less than” and “not greater than” are semantically equivalent.In this case adjustments may also have to be made to the value as “lessthan” does differ from “not greater than” for the boundary condition of18 years of age. As an example, the value “18” may be replaced by thevalue “17.99” in the second rule when “not greater than” is compared forsemantic equivalence with “less than”. This step is shown in FIG. 9 atstep 908.

At step 910, the amended first rule and the amended second rules arecompared for equivalence. This comparison may be an absolute comparisonor it may be a comparison that disregards differences which are eitherminor or of a specified type which does not affect the meaning of therules.

At step 912, responsive to the comparison between the amended first ruleand the amended second rule being true, then the first rule and thesecond rule are identified as being equivalent. Optionally, appropriatechanges may be made to the rules database to ensure that future rulesequivalent to the first and second rule use the preferred terms. Theprocess ends at step 914.

The various function aspects of the disclosure are carried out byexecution of program code and/or program instructions on a processor ofa computer or data processing system (DPS). FIG. 10 illustrates anexample data processing system, which includes processor 1005, memory1010, and storage device 1015, which are all communicativelyinterconnected via a system bus or interconnect 1020. Within memory 1010are one or more applications and or executable modules, includingdecision definition application/module 1025, which executes on processor1005 to configure the processor to perform the various processesdescribed herein. Storage device 1015 includes therein rules vocabulary108, among other stored components. DPS 100 also comprises one or moreinput/output devices, including general input device 1030 and generaloutput device 1035, which are also communicatively coupled to processor1005 via system interconnect 1020. As shown, DPS 1000 can be connectedto an external network 1050 via a network interfacing card (NIC) 1040.

In each of the flow charts above, one or more of the methods may beembodied in a computer readable medium containing computer readable codesuch that a series of steps are performed when the computer readablecode is executed on a computing device. In some implementations, certainsteps of the methods are combined, performed simultaneously or in adifferent order, or perhaps omitted, without deviating from the spiritand scope of the disclosure. Thus, while the method steps are describedand illustrated in a particular sequence, use of a specific sequence ofsteps is not meant to imply any limitations on the disclosure. Changesmay be made with regards to the sequence of steps without departing fromthe spirit or scope of the present disclosure. Use of a particularsequence is therefore, not to be taken in a limiting sense, and thescope of the present disclosure is defined only by the appended claims.

As will be appreciated by one skilled in the art, aspects of the presentdisclosure may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present disclosure may take theform of an entirely hardware embodiment or an embodiment combiningsoftware (including, for example, firmware, resident software,micro-code, etc.) and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,aspects of the present disclosure may take the form of a computerprogram product embodied in one or more computer readable storagedevices or other computer readable medium(s) having computer readableprogram code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage device. A computer readablestorage device may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage device would include the following: a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), a portable compact disc read-only memory (CD-ROM), an opticalstorage device, a magnetic storage device, or any suitable combinationof the foregoing. In the context of this document, a computer readablestorage device may be any tangible medium that can contain or store aprogram for use by or in connection with an instruction executionsystem, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage device and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, R.F, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present disclosure may be written in any combination ofone or more programming languages, including an object orientedprogramming language such as Java, Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

Aspects of the present disclosure are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions can configure a computer, otherprogrammable data processing apparatus, or other devices to function ina particular manner, such that the instructions stored in the computerreadable medium produce an article of manufacture including instructionswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks. The computer program instructions may also beloaded onto a computer, other programmable data processing apparatus, orother devices to cause a series of operational steps to be performed onthe computer, other programmable apparatus or other devices to produce acomputer implemented process such that the instructions which execute onthe computer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The article of manufacture containing the programming code is used byeither executing the code directly from the storage device, by copyingthe code from the storage device into another storage device such as ahard disk, RAM, etc., or by transmitting the code for remote executionusing transmission type media such as digital and analog communicationlinks. The methods of the disclosure may be practiced by combining oneor more machine-readable storage devices containing the code accordingto the present disclosure with appropriate processing hardware toexecute the code contained therein. An apparatus for practicing thedisclosure could be one or more processing devices and storage systemscontaining or having network access to program(s) coded in accordancewith the disclosure.

Thus, it is important that while an illustrative embodiment of thepresent disclosure is described in the context of a fully functionalcomputer (server) system with installed (or executed) software, thoseskilled in the art will appreciate that the software aspects of anillustrative embodiment of the present disclosure are capable of beingdistributed as a program product in a variety of forms, and that anillustrative embodiment of the present disclosure applies equallyregardless of the particular type of media used to actually carry outthe distribution.

While the disclosure has been described with reference to exemplaryembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted forelements thereof without departing from the scope of the disclosure. Inaddition, many modifications may be made to adapt a particular system,device or component thereof to the teachings of the disclosure withoutdeparting from the essential scope thereof. Therefore, it is intendedthat the disclosure not be limited to the particular embodimentsdisclosed for carrying out this disclosure, but that the disclosure willinclude all embodiments falling within the scope of the appended claims.Moreover, the use of the terms first, second, etc. do not denote anyorder or importance, but rather the terms first, second, etc. are usedto distinguish one element from another.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present disclosure has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the disclosure in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of the disclosure and the practical application, and toenable others of ordinary skill in the art to understand the disclosurefor various embodiments with various modifications as are suited to theparticular use contemplated.

While particular embodiments of the present disclosure have been shownand described, it will be obvious to those skilled in the art that,based upon the teachings herein, changes and modifications may be madewithout departing from this disclosure and its broader aspects.Consequently, the appended claims are to encompass within their scopeall such changes and modifications as are within the true spirit andscope of this disclosure and embodiments of the disclosure are intendedto be limited only by the scope of the appended claims, giving fullcognizance to equivalents in all respects.

1. A computer-implemented method of decision definition using a rulesvocabulary, the method comprising the steps of: receiving free forminput; a data processing system identifying terms contained within thefree form input; searching the rules vocabulary objects for terms;responsive to the term being found, obtaining (518) input from a user asto whether to use the found term; responsive to the term not beingfound: searching the rules vocabulary attributes for other terms havingattributes corresponding to the term that is not found; responsive toanother term being found, obtaining input from a user as to whether touse the found similar term; and refactoring the free form input with thefound term or the other term accepted by the user.
 2. The method ofclaim 1, wherein said terms include one of objects, attributes, values,relationships, and verbs.
 3. The method of claim 1, further comprisingupdating said rules vocabulary with said term identified in said freeform input.
 4. The method of claim 1, further comprising updating saidrules vocabulary with said term identified in said free form input as asynonym for said term found in said rules vocabulary.
 5. The method ofclaim 1, wherein responsive to receipt of an input from said user to notuse the term found during the search of the rule vocabulary objects forterms, searching the rules vocabulary attributes for other terms havingattributes corresponding to the found term.
 6. A computer programproduct comprising a computer-readable storage device havingcomputer-readable program code embodied therewith, the computer programcode configured to cause a data processing system to perform theprocesses of claim
 1. 7. A computer program product comprising acomputer-readable storage device having computer-readable program codeembodied therewith, the computer program code configured to cause a dataprocessing system to perform the processes of claim
 3. 8. A computerprogram product comprising a computer-readable storage device havingcomputer-readable program code embodied therewith, the computer programcode configured to cause a data processing system to perform theprocesses of claim
 4. 9. A computer program product comprising acomputer-readable storage device having computer-readable program codeembodied therewith, the computer program code configured to cause a dataprocessing system to perform the processes of claim
 5. 10. A method ofdetermining semantic equivalence between a plurality of rules using arules vocabulary having preferred terms, the method comprising:identifying at least one of objects, attributes, values, relationships,and verbs in each of said plurality of rules; replacing each of said atleast one of objects, attributes, values, relationships or verbs in eachof said plurality of rules with a preferred term found in the rulesdatabase to form a plurality of respective amended rules; comparing afirst of said plurality of amended rules and a second of said pluralityof amended rules; and responsive to said comparison being true, thenidentifying a first of said plurality of rules and a second of saidplurality of rules as being equivalent.
 11. The method of claim 6,further comprising replacing generalised terms with semanticallyequivalent terms.
 12. A computer program product comprising acomputer-readable storage device having computer-readable program codeembodied therewith, the computer program code configured to cause a dataprocessing system to perform the processes of claim
 6. 13. A computerprogram product comprising a computer-readable storage device havingcomputer-readable program code embodied therewith, the computer programcode configured to cause a data processing system to perform theprocesses of claim
 7. 14. A system for decision definition, the systemcomprising: a storage device having: a rules vocabulary containingpreferred terms for objects and for attributes; a local vocabulary; anda rule expressed in free form input, wherein the free form inputcomprises terms which are searched for in the rules vocabulary preferredterms for objects; and a processor executing instructions thatconfigures the system to: search for in the rules vocabulary preferredterms for objects; responsive to the term being found, obtaining inputfrom a user indicating whether to use the found term, and responsive toacceptance by the user, refactor said rule expressed in free form inputwith the found term accepted by the user; responsive (510) to the termnot being found, search the rules vocabulary attributes are searched(512) for terms having attributes corresponding to the term; andresponsive (514) to the term being found obtaining input from a userindicating whether to use the found term; and responsive to acceptanceby the user, refactor said rule expressed in free form input with thefound term accepted by the user.
 15. The system of claim 14, whereinsaid terms are one or more of objects, attributes, values,relationships, and verbs.
 16. The system of claim 14, wherein saidprocessor executes instructions that cause the system to update therules vocabulary is with said term identified in said free form input.17. The system of claim 14, wherein said processor executes instructionsthat cause the system to update said rules vocabulary with said termidentified in said free form input as a synonym for said term found insaid rules vocabulary.
 18. The system of claim 14, wherein responsive toinput from said user to not use the term found during the search of therule vocabulary objects for terms, said processor executes instructionsthat causes the system to search the rules vocabulary attributes forterms having attributes corresponding to the term.
 19. The system ofclaim 14, wherein: each of said rules include at least one of objects,attributes, values, relationships, and verbs; the rules vocabularyincludes preferred terms replacing each of said at least one of objects,attributes, values, relationships or verbs in each of said rules to forman amended rule; and said processor executes instructions that cause thesystem to determine semantic equivalence between a plurality of rulesusing a rules vocabulary having preferred terms by: comparing an amendedfirst one of said plurality of rules and an amended second one of saidplurality of rules; and responsive to said comparing evaluating to beingtrue, identifying said first rule and said second rule as beingequivalent.
 20. The system of claim 19, wherein said processor executesinstructions that cause the system to replace generalized terms withsemantically equivalent terms.